Optical coherence tomography (OCT) is widely recognized as a powerful ophthalmic imaging technique. Optical coherence tomography (OCT) angiography techniques, such as optical microangiography (OMAG), speckle variance, phase variance, etc., use OCT systems to achieve the imaging of flow and motion within a tissue, including imaging of functional vascular networks within microcirculatory tissue beds in vivo, without the use of exogenous contrast agents. A majority of ocular diseases may lead to abnormality in microvasculature beds in the eye, including diabetic retinopathy (DR), age-related macular degeneration (AMD), glaucoma, retinal vein occlusion etc. OCT angiography can be a non-invasive way to be able to diagnose and monitor such vascular abnormalities. However, it is very critical to be able to obtain high quality images of vasculature and perform reliable analysis for diagnosis and monitoring of diseases.
There are several limitations in the state-of-the-art OCT angiography technology that makes it difficult to consistently acquire high quality clinical data sets. One of the major challenges of OCT angiography for larger field of view (FOV) scans is the variability of signal levels from different regions of the eye. This variability can be caused by many factors including subject motion and non-optimized refractive correction in different regions of eye. On the analysis side, there are several challenges as well, such as the capability to segment tissue layers with greater accuracy. Sometimes, spatially localized opacity, such as the one caused by a floater in the vitreous or by the opacity of the lens of the eye, may project dark pockets in the vasculature beds, thereby causing uncertainty in the diagnosis whether it is the loss of vasculature (ischemia) or shadow by a floater. In addition it will also be desirable to be able to develop analyses that could aid in detecting early vasculature based symptoms due to a disease like DR.